Intercept incompatible assumptions between co-running AI subagents before they crash production. TCAS-grade collision detection for the agentic era.
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CROSSFIRE is not just another monitoring tool. It's a TCAS-grade
collision avoidance system purpose-built for the era of parallel AI agents.
When Agent A assumes discount is float[0.0, 1.0]
and Agent B assumes int[0, 100], CROSSFIRE detects the
invariant drift before it reaches production — and issues a
Resolution Advisory to correct it.
$ crossfire verify --path tests/fixtures/ ┌─────────────────┬────────────────────┬──────────┬─────────┐ │ Symbol │ Collision Class │ Severity │ Halted │ ├─────────────────┼────────────────────┼──────────┼─────────┤ │ discount │ INVARIANT_DRIFT │ 0.95 │ ✓ │ │ evict_session │ LIFECYCLE_DESYNC │ 0.85 │ ✓ │ │ get_item │ CONTRACT_DIVERGENCE│ 0.90 │ ✓ │ └─────────────────┴────────────────────┴──────────┴─────────┘ ⚠ 3 collision(s) detected — HALTING agent execution. Resolution Advisory: ▸ discount: Normalize Agent B to float[0.0, 1.0] domain ▸ evict_session: Align Agent B to async lifecycle ▸ get_item: Update Agent A to raise ItemNotFoundError
AST-level extraction of invariant claims from agent scratchpads using Python's ast.NodeVisitor.
Cross-agent collision detection across 3 collision classes — invariant drift, lifecycle desync, contract divergence.
TCAS-grade Resolution Advisories with imperative patch hints and target agent identification.